retoorandClaude Sonnet 5
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- Plexer: always-active terminal multiplexing. NativePlexerController/ TmuxPlexerController share one interface, chosen by which env var is already set (TAI_PLEXER_SOCKET vs TMUX_PANE); NativePlexerBackend is the pty.fork()-based wrapper (raw mode, SIGWINCH resize forwarding, a Unix-socket control protocol, continuous session logging, a Ctrl+A prefix key distinct from tmux's own Ctrl+B). Auto-wraps new interactive shells via a .bashrc hook mirroring the existing command-not-found install pattern, gated on $TMUX/$TAI_PLEXER_ACTIVE/ a $HOME/.tai-no-plexer bypass. New plexer_send/read/type/status tools, env-gated on a detected controller. - tests/container.py + docker-compose.yml + tests/docker/Dockerfile: a disposable podman/docker image for the tests that must never touch a real machine (installing the plexer hook into a real ~/.bashrc, a live tmux session). Required suite (test_seal.py, test_tai.py, tests/plexer.py, tests/bashrc.py) gates the result; tests/rag.py runs as best-effort since its real-LLM dependency can't be satisfied inside a disposable container with no nested engine. - tests/bashrc.py: real end-to-end hook install + bash -i auto-wrap, anti-recursion, tmux-active skip, non-interactive skip, a live TmuxPlexerController test, and an install/uninstall round-trip. - tests/plexer.py: NativePlexerBackend under a real pty, plus a dedicated robustness pass (file permissions, >64KB payload framing, a malformed control request, a genuine self-deadlock fix in the write-to-child path). - tai_test.py: the shared async process-driving framework (pipe/pty transport, group-wide kill-and-reap, a StdinBridge for --interactive) both test files build on. - ChatClient last-resort backend: when there's no local opencode CLI but the sandbox box is already running, install opencode into it (official Node tarball, not apt -- apt's nodejs/npm pull in webpack/babel/jest as transitive deps) and route through it instead of giving up. Only reachable after the first retry round already failed everything else; never creates the box itself. TmuxPlexerController.status() fixed to use `list-panes` instead of `display-message -p`, which silently fell back to the default pane instead of erroring against a dead target. - Fix 4 pre-existing test_tai.py bugs surfaced by running it in a clean environment for the first time: two stale mock signatures (subprocess.run's stdout= kwarg, Chat.complete's deadline= kwarg), one $TMUX-dependent catalog assertion, one tty-dependent color assertion. - research/: a sourced research archive (Source Dossier/Citation Card/Conclusion tiers) backing the above design decisions, with its own audit.py consistency checker. - .gitignore: fix a blanket *.md rule that was about to silently drop the entire research/ archive from version control; add __pycache__/ and the one-off debug transcript this session started from. Co-Authored-By: Claude Sonnet 5 <noreply@anthropic.com>
51 lines
2.7 KiB
Markdown
51 lines
2.7 KiB
Markdown
# Memory eviction and forgetting in AI agents
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## Metadata
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| Field | Value |
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| Institute | Molodetz Institute — Research & Retrieval Division |
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| Subject | agent-memory-recency-tracking |
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| Document type | Source Dossier |
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| Tier | 1 |
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| Source title | Memory eviction and forgetting in AI agents |
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| Source URL | https://mem0.ai/blog/memory-eviction-and-forgetting-in-ai-agents |
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| Source publisher / author | Mem0 (vendor blog) |
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| Source type | blog post / vendor docs |
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| Source date (published) | Unknown — not stated |
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| Date researched | 2026-10-09 |
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| Researched by | tai (agent), model: Claude Sonnet 5, on behalf of retoor |
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| Research method | web search synthesis |
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| Confidence | Medium |
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| Status | Active |
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## Summary
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Mem0's broader guidance on eviction/forgetting beyond the Memory Decay feature specifically: it distinguishes soft re-ranking (decay) from real pruning, and recommends TTL policies plus explicit deletion APIs for genuine forgetting, with tiered memory lifetimes by scope.
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## Key findings
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- Session memory is described as persisting minutes-to-hours and being cleared explicitly; user- and organization-level memory are long-lived by contrast.
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- For episodic data specifically, the guidance is to use timestamps plus explicit TTL policies rather than relying on decay alone.
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- The source explicitly states memory systems need deletion APIs and UX patterns that expose what is remembered — i.e. forgetting should be an observable, intentional operation, not an opaque side effect.
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- Decay (see `mem0-introducing-memory-decay.md`) is characterized here as "decays low-relevance entries over time, freeing up space and attention" — a description, not a documented formula.
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## Pros / strengths
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- Clearly separates three distinct concerns that are easy to conflate: ranking (decay), lifecycle/expiry (TTL), and user-visible deletion (explicit API) — a useful three-way framework for tai to keep in mind even though only the tracking substrate for the first concern is being built right now.
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## Cons / limitations / caveats
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- Lacks a documented formula for its own decay mechanism (consistent with the companion decay-announcement post); this source is guidance-level, not implementation-level detail.
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- Vendor content, not independently verified.
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## Relevance to tai
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Useful for correctly scoping what tai's `last_used`/`use_count` proposal is and is not: it is tracking substrate that could later feed a decay-style ranking signal (per Mem0's own distinction), but it is explicitly not a TTL/expiry mechanism and not a deletion mechanism — those would be separate, later decisions if ever made.
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## Changelog
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| Date | Change |
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| 2026-10-09 | Initial dossier created. |
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